Construct Validity and Test–Retest Reliability of the Automated Vehicle User Perception Survey

Academic Article


  • Fully automated vehicles (AVs) hold promise toward providing numerous societal benefits including reducing road fatalities. However, we are uncertain about how individuals’ perceptions will influence their ability to accept and adopt AVs. The 28-item Automated Vehicle User Perception Survey (AVUPS) is a visual analog scale that was previously constructed, with established face and content validity, to assess individuals’ perceptions of AVs. In this study, we examined construct validity, via exploratory factor analysis and subsequent Mokken scale analyses. Next, internal consistency was assessed via Cronbach’s alpha (α) and 2-week test–retest reliability was assessed via Spearman’s rho (ρ) and intraclass correlation coefficient (ICC). The Mokken scale analyses resulted in a refined 20-item AVUPS and three Mokken subscales assessing specific domains of adults’ perceptions of AVs: (a) Intention to use; (b) perceived barriers; and (c) well-being. The Mokken scale analysis showed that all item-coefficients of homogeneity (H) exceeded 0.3, indicating that the items reflect a single latent variable. The AVUPS indicated a strong Mokken scale (Hscale = 0.51) with excellent internal consistency (α = 0.95) and test–retest reliability (ρ = 0.76, ICC = 0.95). Similarly, the three Mokken subscales ranged from moderate to strong (range Hscale = 0.47–0.66) and had excellent internal consistency (range α = 0.84–0.94) and test–retest reliability (range ICC = 0.84–0.93). The AVUPS and three Mokken subscales of AV acceptance were validated in a moderate sample size (N = 312) of adults living in the United States. Two-week test–retest reliability was established using a subset of Amazon Mechanical Turk participants (N = 84). The AVUPS, or any combination of the three subscales, can be used to validly and reliably assess adults’ perceptions before and after being exposed to AVs. The AVUPS can be used to quantify adults’ acceptance of fully AVs.
  • Published In

    Digital Object Identifier (doi)

    Author List

  • Mason J; Classen S; Wersal J; Sisiopiku V
  • Volume

  • 12